> For the complete documentation index, see [llms.txt](https://george-jen.gitbook.io/data-science-and-apache-spark/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://george-jen.gitbook.io/data-science-and-apache-spark/graphx-example-2.md).

# Graphx Example 2

### pageRank example

Given user data in users.txt and follower data in followers.txt, with the column name is as illustrated, calculate pageRank with tolerence at 0.0001 for each user, sort the output by rank.

### users.txt (user id, username, name)

```
1,BarackObama,Barack Obama 
2,ladygaga,Goddess of Love 
3,jeresig,John Resig 
4,justinbieber,Justin Bieber 
6,matei_zaharia,Matei Zaharia 
7,odersky,Martin Odersky 
8,anonsys
```

### followers.txt: (follower user id, to be followed user id)

```
2 1 
4 1 
1 2 
6 3 
7 3 
7 6 
6 7 
3 7
```

Code:

```
import org.apache.spark._
import org.apache.spark.graphx._
import org.apache.spark.rdd.RDD
import org.apache.spark.graphx.GraphLoader

// Load the edges as a graph
val graph = GraphLoader.edgeListFile(sc, "file:///home/dv6/spark/spark/data/graphx/followers.txt")
// Run PageRank, with 0.0001 as tolerence 

val ranks = graph.pageRank(0.0001).vertices

ranks.foreach(println)
/*
user id, ranking
(4,0.15007622780470478)
(6,0.7017164142469724)
(2,1.3907556008752426)
(1,1.4596227918476916)
(3,0.9998520559494657)
(7,1.2979769092759237)
*/

// Join the ranks with the usernames
val users = sc.textFile("file:///home/dv6/spark/spark/data/graphx/users.txt").map { line =>
  val fields = line.split(",")
  (fields(0).toLong, fields(1))
}
val ranksByUsername = users.join(ranks).map {
  case (id, (username, rank)) => (username, rank)
}

ranksByUsername.foreach(println)

/*
Output:
(BarackObama,1.4596227918476916)
(jeresig,0.9998520559494657)
(odersky,1.2979769092759237)
(justinbieber,0.15007622780470478)
(matei_zaharia,0.7017164142469724)
(ladygaga,1.3907556008752426)

*/

//Sortby ranking

ranksByUsername.toDF.withColumnRenamed("_1","username")
         .withColumnRenamed("_2","rank")
          .createOrReplaceTempView("ranksByusername")
spark.sql("select * from ranksByusername order by rank desc").show()
/*
Output:
+-------------+-------------------+
|     username|               rank|
+-------------+-------------------+
|  BarackObama| 1.4596227918476916|
|     ladygaga| 1.3907556008752426|
|      odersky| 1.2979769092759237|
|      jeresig| 0.9998520559494657|
|matei_zaharia| 0.7017164142469724|
| justinbieber|0.15007622780470478|
+-------------+-------------------+



*/
```


---

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